code: def conv_deformable(
      net, num_filter, num_group=1, act_type="relu", name=""
  ):
      f = num_group * 18
      conv_offset = mx.symbol.Convolution(
          name=name + "_conv_offset",
          data=net,
          num_filter=f,
          pad=(1, 1),
          kernel=(3, 3),
          stride=(1, 1),
      )
      net = mx.contrib.symbol.DeformableConvolution(
          name=name + "_conv",
          data=net,
          offset=conv_offset,
          num_filter=num_filter,
          pad=(1, 1),
          kernel=(3, 3),
          num_deformable_group=num_group,
          stride=(1, 1),
          no_bias=False,
      )
      net = mx.sym.BatchNorm(
          data=net,
          fix_gamma=False,
          eps=2e-5,
          momentum=0.9,
          name=name + "_bn",
      )
      if len(act_type) > 0:
          net = mx.symbol.Activation(
              data=net, act_type=act_type, name=name + "_act"
          )
      return net
  
file_path: insightface/detection/retinaface/rcnn/symbol/symbol_resnet.py
imports: import mxnet
  import mxnet.ndarray
  import mxnet.gluon
  import mxnet.gluon.nn
  import mxnet.autograd
  import numpy
  from rcnn.config import config
  from rcnn.PY_OP import rpn_fpn_ohem3
  from rcnn.symbol.symbol_common import get_sym_train
label_desc: Use image node_id 5 for calling a global function with example usage: conv_deformable(net, num_filter, num_group, act_type, name) and returns: net